Netflix
Member of Technical Staff, Agentic Systems - Games
Los Gatos,California,United States of America · Staff+ · Full-time
Sponsorship not specifiedDetected 4 hours ago
PythonMachine LearningData EngineeringLLMsAgentic AILangGraphAI OrchestrationA/B TestingUX ResearchProduct ManagementProduct StrategyUnityUnreal EngineResearch
About the role
- We're seeking a technical leader to help shape the strategy, development & delivery of GenAI tools and agentic systems across Netflix Games.
- Comfortable taking a fine-tuning project from dataset curation through deployment and ongoing maintenance. - Published research or public contributions in agentic systems, RLHF, or LLM evaluation.
Responsibilities
- Derive insights from user research and quantitative data to create product roadmaps, which identify the highest return investments, distinguish hype from value.
- Prototyping to Shipping: Bring product strategy skills and builder capabilities to every initiative, define what's worth building, not just how to build it.
- Prototype fast to validate ideas with real systems, identify where agentic AI genuinely transforms player experience or team productivity, and take features from concept to production without a handoff layer.
- Design and build the code harnesses and scaffolding connecting frontier models (or open-weight alternatives) to tooling, game engines, and platform APIs.
- Build reusable agent primitives and infrastructure, MCPs (Model Context Protocols) and shared agentic libraries, that raise the floor for the whole organization and reduce duplicated effort across game studios and platform teams.
- Define and build online evaluation: A/B testing, production telemetry, user feedback loops, and anomaly detection for agent behavior drift.
- Partner with external researchers, developers, and companies pioneering work in the agentic AI space. Stay on the forefront of emerging frameworks, open models, and infrastructure patterns, and bring those learnings back to accelerate our own efforts.
- Collaborate with our engineering and platform teams to build robust solutions and scale core capabilities: model inference, data pipelines, responsible AI compliance, safety guardrails, and graceful degradation at scale.
Requirements
- 3+ years of experience in the game development industry.
- Product management experience, identifying user needs, defining product roadmaps, running production development workstreams.
- Strong Python engineering skills and production experience with agentic frameworks (LangChain, LangGraph, AutoGen, Google ADK, or equivalent).
- Proven experience designing and operating evaluation infrastructure for AI systems, offline benchmarks, automated scoring pipelines, and online experimentation.
Nice to have
- Familiarity with Model Context Protocol (MCP) or similar agent-to-system connectivity standards.
- Experience with inference optimization for agentic deployments: latency reduction, cost management, streaming responses.
- Background in responsible AI: safety evaluation, prompt injection defense, output moderation, and content policy compliance.
- Experience with the full LLM fine-tuning lifecycle: SFT, DPO, LoRA/QLoRA, and RLHF for long-horizon tasks.
- Comfortable taking a fine-tuning project from dataset curation through deployment and ongoing maintenance.
- Published research or public contributions in agentic systems, RLHF, or LLM evaluation.
- we do not have bonuses.
- To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range.
Skills
- The next challenge for Netflix Games will be applying AI at the scale and quality consumers expect to make real impact.
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This listing is sourced directly from Netflix's careers page and normalized into a canonical job model.